UAV-Hyp: UAV Dataset for Remote Sensing-Based Phenotyping of Hypericum perforatum

Quantitative flowering phenotypes are needed to support breeding and harvest management in Hypericum perforatum L. (St. John’s wort), but manual flower assessment is slow and difficult to standardize under field conditions. UAV-Hyp is a multi-temporal UAV RGB dataset containing 12,653 high-resolution images acquired at 26 measurement dates across the complete flowering period of 15 H. perforatum accessions. The images represent variable illumination, soil moisture, weed pressure, and developmental stages. The dataset provides 59,163 plant bounding boxes and 107,054 flower bounding boxes. As an application example, cascaded YOLOv8 plant and flower detectors achieved [email protected]:0.95 values of 0.977 and 0.950, respectively. UAV-Hyp supports scalable flower quantification and the development of time-series phenotyping methods for genotype comparison and quality-oriented medicinal-plant breeding.

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Published
2026-08-17
DOI
https://doi.org/10.3390/data11080208
Primary Topic
Smart Agriculture and AI
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article
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article

UAV-Hyp: UAV Dataset for Remote Sensing-Based Phenotyping of Hypericum perforatum

Ahmed El Menuawy, Katrin N.E. Fitza, Frank Marthe, Sven Reichardt et al.
Data
Smart Agriculture and AI
article

UAV-Hyp: UAV Dataset for Remote Sensing-Based Phenotyping of Hypericum perforatum

Ahmed El Menuawy, Katrin N.E. Fitza, Frank Marthe, Sven Reichardt, Yujie Zhang
article en

Abstract

Quantitative flowering phenotypes are needed to support breeding and harvest management in Hypericum perforatum L. (St. John’s wort), but manual flower assessment is slow and difficult to standardize under field conditions. UAV-Hyp is a multi-temporal UAV RGB dataset containing 12,653 high-resolution images acquired at 26 measurement dates across the complete flowering period of 15 H. perforatum accessions. The images represent variable illumination, soil moisture, weed pressure, and developmental stages. The dataset provides 59,163 plant bounding boxes and 107,054 flower bounding boxes. As an application example, cascaded YOLOv8 plant and flower detectors achieved [email protected]:0.95 values of 0.977 and 0.950, respectively. UAV-Hyp supports scalable flower quantification and the development of time-series phenotyping methods for genotype comparison and quality-oriented medicinal-plant breeding.

DataVol. 11(8)
Julius Kühn-Institut (DE), University of Siegen (DE)
Fachagentur Nachwachsende Rohstoffe, German Network for Bioinformatics Infrastructure
Openalex Percentile: Top 12%
Smart Agriculture and AI
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